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View article: Large Language Models for Medical Forecasting -- Foresight 2
Large Language Models for Medical Forecasting -- Foresight 2 Open
Foresight 2 (FS2) is a large language model fine-tuned on hospital data for modelling patient timelines (GitHub 'removed for anon'). It can understand patients' clinical notes and predict SNOMED codes for a wide range of biomedical use cas…
View article: Predicting Future Disorders via Temporal Knowledge Graphs and Medical Ontologies
Predicting Future Disorders via Temporal Knowledge Graphs and Medical Ontologies Open
Despite the vast potential for insights and value present in Electronic Health Records (EHRs), it is challenging to fully leverage all the available information, particularly that contained in the free-text data written by clinicians descr…
View article: Foresight—a generative pretrained transformer for modelling of patient timelines using electronic health records: a retrospective modelling study
Foresight—a generative pretrained transformer for modelling of patient timelines using electronic health records: a retrospective modelling study Open
National Health Service Artificial Intelligence Laboratory, National Institute for Health and Care Research Biomedical Research Centre, and Health Data Research UK.
View article: Evaluating clinical outcomes and prognosis in patients with cirrhosis and portal hypertension: a retrospective observational cohort study
Evaluating clinical outcomes and prognosis in patients with cirrhosis and portal hypertension: a retrospective observational cohort study Open
Objective Cirrhosis describes the end-stage of chronic liver disease. Irreversible changes in the liver cause portal hypertension, which can progress to serious complications and death. Only a few studies with small sample sizes have inves…
View article: Implementation of the trial emulation approach in medical research: a scoping review
Implementation of the trial emulation approach in medical research: a scoping review Open
View article: Hospital-wide natural language processing summarising the health data of 1 million patients
Hospital-wide natural language processing summarising the health data of 1 million patients Open
Electronic health records (EHRs) represent a major repository of real world clinical trajectories, interventions and outcomes. While modern enterprise EHR’s try to capture data in structured standardised formats, a significant bulk of the …
View article: Diagnostic signature for heart failure with preserved ejection fraction (HFpEF): a machine learning approach using multi-modality electronic health record data
Diagnostic signature for heart failure with preserved ejection fraction (HFpEF): a machine learning approach using multi-modality electronic health record data Open
Background Heart failure with preserved ejection fraction (HFpEF) is thought to be highly prevalent yet remains underdiagnosed. Evidence-based treatments are available that increase quality of life and decrease hospitalization. We sought t…
View article: Foresight -- Generative Pretrained Transformer (GPT) for Modelling of Patient Timelines using EHRs
Foresight -- Generative Pretrained Transformer (GPT) for Modelling of Patient Timelines using EHRs Open
Background: Electronic Health Records hold detailed longitudinal information about each patient's health status and general clinical history, a large portion of which is stored within the unstructured text. Existing approaches focus mostly…
View article: Hospital-wide Natural Language Processing summarising the health data of 1 million patients
Hospital-wide Natural Language Processing summarising the health data of 1 million patients Open
Electronic health records (EHRs) represent a major repository of real world clinical trajectories, interventions and outcomes. While modern enterprise EHR’s try to capture data in structured standardised formats, a significant bulk of the …
View article: Anticoagulation for atrial fibrillation in people with serious mental illness in the general hospital setting
Anticoagulation for atrial fibrillation in people with serious mental illness in the general hospital setting Open
Over recent years, DOAC prescription rates have increased among AF patients with SMI in acute hospitals. More research is needed to confirm whether the introduction of DOACs has reduced OAC treatment gaps in people with serious mental illn…
View article: Evaluation of antithrombotic use and COVID-19 outcomes in a nationwide atrial fibrillation cohort
Evaluation of antithrombotic use and COVID-19 outcomes in a nationwide atrial fibrillation cohort Open
Objective To evaluate antithrombotic (AT) use in individuals with atrial fibrillation (AF) and at high risk of stroke (CHA 2 DS 2 -VASc score ≥2) and investigate whether pre-existing AT use may improve COVID-19 outcomes. Methods Individual…
View article: Mapping multimorbidity in individuals with schizophrenia and bipolar disorders: evidence from the South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLAM BRC) case register
Mapping multimorbidity in individuals with schizophrenia and bipolar disorders: evidence from the South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLAM BRC) case register Open
Objectives The first aim of this study was to design and develop a valid and replicable strategy to extract physical health conditions from clinical notes which are common in mental health services. Then, we examined the prevalence of thes…
View article: A novel algorithmic approach to generate consensus treatment guidelines in adult acute myeloid leukaemia
A novel algorithmic approach to generate consensus treatment guidelines in adult acute myeloid leukaemia Open
Summary Induction therapy for acute myeloid leukaemia (AML) has changed with the approval of a number of new agents. Clinical guidelines can struggle to keep pace with an evolving treatment and evidence landscape and therefore identifying …
View article: Diagnostic signature for Heart Failure with Preserved Ejection Fraction (HFpEF): A Machine Learning Approach Using Multi-Modality Electronic Health Record Data
Diagnostic signature for Heart Failure with Preserved Ejection Fraction (HFpEF): A Machine Learning Approach Using Multi-Modality Electronic Health Record Data Open
Aims Heart failure with preserved ejection fraction (HFpEF) is thought to be highly prevalent yet remains underdiagnosed. We sought to develop a data-driven diagnostic model to predict from electronic health records (EHR) the likelihood of…
View article: Evaluation of antithrombotic use and COVID-19 outcomes in a nationwide atrial fibrillation cohort
Evaluation of antithrombotic use and COVID-19 outcomes in a nationwide atrial fibrillation cohort Open
Objective Evaluate antithrombotic (AT) use in individuals with atrial fibrillation (AF) and high stroke risk (CHA 2 DS 2 -VASc score>=2) and investigate whether pre-existing AT use may improve COVID-19 outcomes. Methods Individuals with AF…
View article: Regional performance variation in external validation of four prediction models for severity of COVID-19 at hospital admission: An observational multi-centre cohort study
Regional performance variation in external validation of four prediction models for severity of COVID-19 at hospital admission: An observational multi-centre cohort study Open
Background Prediction models should be externally validated to assess their performance before implementation. Several prediction models for coronavirus disease-19 (COVID-19) have been published. This observational cohort study aimed to va…
View article: MedGPT: Medical Concept Prediction from Clinical Narratives
MedGPT: Medical Concept Prediction from Clinical Narratives Open
The data available in Electronic Health Records (EHRs) provides the opportunity to transform care, and the best way to provide better care for one patient is through learning from the data available on all other patients. Temporal modellin…
View article: Pre-existing cardiovascular disease rather than cardiovascular risk factors drives mortality in COVID-19
Pre-existing cardiovascular disease rather than cardiovascular risk factors drives mortality in COVID-19 Open
Background The relative association between cardiovascular (CV) risk factors, such as diabetes and hypertension, established CV disease (CVD), and susceptibility to CV complications or mortality in COVID-19 remains unclear. Methods We cond…
View article: DGLinker: flexible knowledge-graph prediction of disease–gene associations
DGLinker: flexible knowledge-graph prediction of disease–gene associations Open
As a result of the advent of high-throughput technologies, there has been rapid progress in our understanding of the genetics underlying biological processes. However, despite such advances, the genetic landscape of human diseases has only…
View article: Multi-domain clinical natural language processing with MedCAT: The Medical Concept Annotation Toolkit
Multi-domain clinical natural language processing with MedCAT: The Medical Concept Annotation Toolkit Open
View article: Regional performance variation in external validation of four prediction models for severity of COVID-19 at hospital admission: An observational multi-centre cohort study
Regional performance variation in external validation of four prediction models for severity of COVID-19 at hospital admission: An observational multi-centre cohort study Open
Background Several prediction models for coronavirus disease-19 (COVID-19) have been published. Prediction models should be externally validated to assess their performance before implementation. This observational cohort study aimed to va…
View article: An open‐source, expert‐designed decision tree application to support accurate diagnosis of myeloid malignancies
An open‐source, expert‐designed decision tree application to support accurate diagnosis of myeloid malignancies Open
Accurate, reproducible diagnoses can be difficult to make in haemato‐oncology due to multi‐parameter clinical data, complex diagnostic criteria and time‐pressured environments. We have designed a decision tree application (DTA) that reflec…
View article: Biological responses to COVID-19: Insights from physiological and blood biomarker profiles
Biological responses to COVID-19: Insights from physiological and blood biomarker profiles Open
View article: Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study
Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study Open
View article: Additional file 4 of Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study
Additional file 4 of Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study Open
Additional file 4: Table S4. Internally validated discrimination for KCH training sample based on nested repeated cross-validation.
View article: Additional file 1 of Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study
Additional file 1 of Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study Open
Additional file 1: Table S1. SNOMED terms.
View article: Additional file 3 of Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study
Additional file 3 of Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study Open
Additional file 3: Table S3. Logistic regression models for each blood and physiological measure tested separately in the KCH training cohort, for 14- and 3-day ICU/death.
View article: Additional file 7 of Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study
Additional file 7 of Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study Open
Additional file 7: Table S6. Discrimination for all models in training and validation cohorts, including alternative baseline model of ‘NEWS2 only’.
View article: Additional file 2 of Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study
Additional file 2 of Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study Open
Additional file 2: Table S2. F1, precision and recall for NLP comorbidity detection.
View article: Additional file 6 of Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study
Additional file 6 of Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study Open
Additional file 6: Table S5. Univariate logistic regression models for sensitivity analyses showing odds ratios of ICU/death at 3- and 14-days for subsets of the training cohort.